A survey of learning-based techniques of email spam filtering

By Enrico Blanzieri, Anton Bryl. Artificial Intelligence Review, 2008

448 citations recorded by the source corpus.

How researchers see this paper

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Community Targeted Spam: A Middle Ground Between General Spam and Spear Phishing (2017, background): “That being said, spam filters are proving themselves more and more reliable [7] [8] and the only way that spammers have to trick such advanced filters is to produce better emails.”
A survey of the applications of text mining in financial domain (2016, background): “Shravan Kumar , Vadlamani Ravi PII: S0950-7051(16)30387-2 DOI: 10.”
A review of machine learning approaches to Spam filtering (2009, methodology): “A more recent review has been conducted by Blanzieri and Bryl (2008).”
Malicious URL Detection using Machine Learning: A Survey (2017, background): “Other recent learning based spam detection surveys include [162]–[164], many of which focus on spam appearing in online reviews.”
Natural language processing: state of the art, current trends and challenges (2017, background): “that even though a great amount of work on natural language processing is available in literature surveys (one may refer to [15, 32, 63, 98, 133, 151] focusing on one domain such as usage of deep-learning techniques in NLP, techniques used for email spam filtering, medication safety, management rese”
Outlier Analysis (2013, methodology): “A survey of methods for email spam filtering may be found in [67, 124].”